3.
SRE Tools: SMERFS /1
• Statistical Modeling and Estimation of Reliability Functions
for Software
• SMERFS is a public-domain software package designed and
implemented at the Naval Surface Warfare Center.
• SMERFS is a program for estimating and predicting the
reliability of software during the testing phase.
• It uses failure count information to make these predictions

5.
SRE Tools: SMERFS /3
• History file is an output file created by SMERFS. It is a trace
file that contains all of the user input and SMERFS outputs for
a particular run so that the user can go back and look at the run
at a later time.
• Plot file contains the raw output data in plotting results

6.
SRE Tools: SMERFS /4
• Input data file contains the failure history data on which
SMERFS will actually operate to produce the reliability
estimates and predictions.
• The user must also specify the type of data contained in the
input data.
• If the selected data type does not correspond to the type of data
actually in the input file, the estimates and predictions made by
SMERFS will not be valid.

7.
SRE Tools: SMERFS /5
• Output data file is a file that the user can specify to which
SMERFS will write failure history data created or edited by
the user during the current SMERFS session.
• This is different from the history file, since the history file is a
trace file which records all user input and SMERFS responses.
• The output data file can be used in subsequent sessions as an
input data file.
• The output file is in SMERFS format, not ASCII format.

8.
SRE Tools: SRMP /1
Statistical Modeling and Reliability Program
• The SRMP was developed by the Reliability and Statistical
Consultants, Limited of UK in 1988.
• SRMP is a command-line-oriented tool developed for an IBM
PC/AT and also UNIX based workstations.
• SRMP contains nine models.
• SRMP uses the maximum likelihood estimation technique to
compute the model parameters, and provides the following
reliability indicators:
reliability function, failure rate, mean time to failure,
median time to failure, and the model parameters for each
model.

9.
SRE Tools: SRMP /2
• SRMP requires an ASCII data file as input.
• The file contains the name (or other identification) of the
project, the number of failures involved in the reliability
analysis, and the inter-failure times of all the failures.
• The input file also specifies the initial sample size used by
SRMP for the initial fitting of each reliability model to the data.
• The remaining failures are used by SRMP for assessing a
reliability model's prediction accuracy.

11.
SRE Tools: SoftRel /2
• The fundamental difference is that SoftRel is a simulation tool,
rather than a reliability growth modeling tool, i.e., one can
simulate the interdependencies between components.
• Example: what will be the effect of producing more
documentation vs. more coding? (assuming requirementdesign-coding-test lifecycle)
• SoftRel uses Piecewise-Poisson Markov Process to simulate
project occurrences
• Limitations: SoftRel is limited to studying a project that has
the standard waterfall lifecycle.

12.
SRE Tools: CASRE /1
Computer-Aided Software Reliability Estimation Tool
• CASRE is copyrighted by NASA.
• CASRE is a PC-based tool that was developed in 1993 by the
Jet Propulsion Laboratories to address the ease-of-use issues of
other tools.
• CASRE requires the WINDOWS operating environment.
• Four combined models are permanently available in CASRE.
• CASRE ver. 3.0 is available

13.
SRE Tools: CASRE /2
• CASRE allows an analyst to invoke a text editor or other
application from within CASRE to create the ASCII input data
set. The input data set contains fields for the test interval
number, number of failures observed in the interval, length of
the test interval, fraction of the program tested, and severity of
the failure.
• Once the data is entered, CASRE automatically provides the
analyst with a raw data plot.
• CASRE provides the analyst with the ability to convert from
time-domain data to interval-domain data and vice versa.

14.
SRE Tools: CASRE /3
• CASRE
provides
operations
to
transform or smooth
the failure data; the
user can select and/or
define
multiple
models
for
application to the data
and make reliability
predictions based on
the best model.
Figure from SRE Handbook

22.
INITIAL AND LATER STATES
•
•
•
•
•
•
Failure to initialize a data item to zero
Failure to initialize a loop-control variable
Failure to initialize(or reinitialize) a pointer
Failure to clear a string
Failure to initialize(or reinitialize) registers
Failure to clear a flag

23.
RACE CONDITIONS
• Assumption that one event or task has finished before another
begins
• Assumption that input won’t occur during a brief processing
interval
• Assumption that interrupts won’t occur during a brief interval
• Resource races: the resource has just become unavailable

24.
LOAD CONDITIONS
•
•
•
•
Required resources not available
No available large memory areas
Input buffer or queue not deep enough
Lost messages